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    Sequence-Based Prediction of Protein–Carbohydrate Binding Sites Using Support Vector Machines
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    † ‡ †School of Information and Communication Technology and ‡Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4215, Australia
    *E-mail: [email protected]
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    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2016, 56, 10, 2115–2122
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    https://doi.org/10.1021/acs.jcim.6b00320
    Published September 13, 2016
    Copyright © 2016 American Chemical Society
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    Abstract

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    Carbohydrate-binding proteins play significant roles in many diseases including cancer. Here, we established a machine-learning-based method (called sequence-based prediction of residue-level interaction sites of carbohydrates, SPRINT-CBH) to predict carbohydrate-binding sites in proteins using support vector machines (SVMs). We found that integrating evolution-derived sequence profiles with additional information on sequence and predicted solvent accessible surface area leads to a reasonably accurate, robust, and predictive method, with area under receiver operating characteristic curve (AUC) of 0.78 and 0.77 and Matthew’s correlation coefficient of 0.34 and 0.29, respectively for 10-fold cross validation and independent test without balancing binding and nonbinding residues. The quality of the method is further demonstrated by having statistically significantly more binding residues predicted for carbohydrate-binding proteins than presumptive nonbinding proteins in the human proteome, and by the bias of rare alleles toward predicted carbohydrate-binding sites for nonsynonymous mutations from the 1000 genome project. SPRINT-CBH is available as an online server at http://sparks-lab.org/server/SPRINT-CBH.

    Copyright © 2016 American Chemical Society

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    Cite this: J. Chem. Inf. Model. 2016, 56, 10, 2115–2122
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jcim.6b00320
    Published September 13, 2016
    Copyright © 2016 American Chemical Society
    Request reuse permissions

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